Citation:

PANGAEA.923270

Name: Manually delineated calving fronts at Jakobshavn Isbræ, Kangerlussuaq, and Helheim
Published: 2020-09-30
License: https://creativecommons.org/licenses/by/4.0/
Keywords: calving front; deep learning; glacier; Greenland

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Abstract:

This dataset contains manually-delineated calving front positions at Jakobshavn Isbræ, Kangerlussuaq, Helheim, covering from 2003 to 2019. These manually-delineated calving fronts are for training, validating, and testing our deep learning network. The format of this dataset is Shapefile.

Keyword(s):

calving front; deep learning; glacier; Greenland

Related to:

Zhang, Enze; Liu, Lin; Huang, Lingcao; Ng, Ka Shing (in prep.): An automated, generalized, deep-learning-based method for delineating calving fronts of Greenland glaciers from multi-sensor remote sensing imagery. Remote Sensing of Environment

Coverage:

Median Latitude: 67.515167 * Median Longitude: -46.230700 * South-bound Latitude: 66.366100 * West-bound Longitude: -50.713000 * North-bound Latitude: 69.171400 * East-bound Longitude: -38.195500

Event(s):

Helheim_glacier * Latitude: 66.366100 * Longitude: -38.195500 * Location: Sermilik Fjord, SE Greenland * Method/Device: Multiple investigations (MULT)

Jakobshavn_Isbrae * Latitude: 69.171400 * Longitude: -49.783600 * Location: West Greenland * Method/Device: Multiple investigations (MULT)

Kangerlussuaq_settlem (KAN) * Latitude: 67.008000 * Longitude: -50.713000 * Location: Greenland

Parameter(s):

#	Name	Short Name	Unit	Principal Investigator	Method/Device	Comment
1	Event label	Event		Zhang, Enze
2	Binary Object	Binary		Zhang, Enze

License:

Creative Commons Attribution 4.0 International (CC-BY-4.0)

Size:

3 data points

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